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Add detailed logging for LLM message handling and API requests #815

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467878b
Add detailed logging for LLM message handling and API requests
Jul 3, 2025
b5e3942
addlog
Jul 15, 2025
88044eb
Merge branch 'voideditor:main' into mydev
osanben Jul 15, 2025
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5 changes: 5 additions & 0 deletions src/vs/workbench/api/common/extHostSearch.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -158,6 +158,7 @@ export class ExtHostSearch implements IExtHostSearch {
}

$provideTextSearchResults(handle: number, session: number, rawQuery: IRawTextQuery, token: vscode.CancellationToken): Promise<ISearchCompleteStats> {
console.log('[ExtHostSearch] $provideTextSearchResults called', { handle, session, rawQuery });
const provider = this._textSearchProvider.get(handle);
if (!provider || !provider.provideTextSearchResults) {
throw new Error(`Unknown Text Search Provider ${handle}`);
Expand All @@ -169,11 +170,15 @@ export class ExtHostSearch implements IExtHostSearch {
}

$provideAITextSearchResults(handle: number, session: number, rawQuery: IRawAITextQuery, token: vscode.CancellationToken): Promise<ISearchCompleteStats> {
this._logService.info('[ExtHostSearch] $provideAITextSearchResults called', handle, session);

const provider = this._aiTextSearchProvider.get(handle);
if (!provider || !provider.provideAITextSearchResults) {
this._logService.error(`Unknown AI Text Search Provider ${handle}`);
throw new Error(`Unknown AI Text Search Provider ${handle}`);
}

this._logService.info('[ExtHostSearch] Provider found, creating TextSearchManager');
const query = reviveQuery(rawQuery);
const engine = this.createAITextSearchManager(query, provider);
return engine.search(progress => this._proxy.$handleTextMatch(handle, session, progress), token);
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24 changes: 24 additions & 0 deletions src/vs/workbench/contrib/void/browser/chatThreadService.ts
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Expand Up @@ -802,6 +802,16 @@ class ChatThreadService extends Disposable implements IChatThreadService {
let resMessageIsDonePromise: (res: ResTypes) => void // resolves when user approves this tool use (or if tool doesn't require approval)
const messageIsDonePromise = new Promise<ResTypes>((res, rej) => { resMessageIsDonePromise = res })

// 日志：Browser端 - LLM请求开始
console.log('🔥 [Browser] LLM Chat Request Starting =====================================')
console.log('🔥 [Browser] Thread ID:', threadId)
console.log('🔥 [Browser] Chat Mode:', chatMode)
console.log('🔥 [Browser] Model Selection:', modelSelection)
console.log('🔥 [Browser] Messages Count:', messages.length)
console.log('🔥 [Browser] Separate System Message Length:', separateSystemMessage?.length || 0)
console.log('🔥 [Browser] Messages Preview:', messages.slice(-2)) // 显示最后2条消息
console.log('🔥 [Browser] =====================================')

const llmCancelToken = this._llmMessageService.sendLLMMessage({
messagesType: 'chatMessages',
chatMode,
Expand All @@ -812,16 +822,30 @@ class ChatThreadService extends Disposable implements IChatThreadService {
logging: { loggingName: `Chat - ${chatMode}`, loggingExtras: { threadId, nMessagesSent, chatMode } },
separateSystemMessage: separateSystemMessage,
onText: ({ fullText, fullReasoning, toolCall }) => {
// 更新状态，不打印流式日志
this._setStreamState(threadId, { isRunning: 'LLM', llmInfo: { displayContentSoFar: fullText, reasoningSoFar: fullReasoning, toolCallSoFar: toolCall ?? null }, interrupt: Promise.resolve(() => { if (llmCancelToken) this._llmMessageService.abort(llmCancelToken) }) })
},
onFinalMessage: async ({ fullText, fullReasoning, toolCall, anthropicReasoning, }) => {
// 日志：Browser端 - 最终响应
console.log('🔥 [Browser] LLM Response Complete =====================================')
console.log('🔥 [Browser] Final Text Length:', fullText.length)
console.log('🔥 [Browser] Final Text:', fullText)
console.log('🔥 [Browser] Final Reasoning Length:', fullReasoning?.length || 0)
console.log('🔥 [Browser] Final Tool Call:', toolCall)
console.log('🔥 [Browser] Anthropic Reasoning:', anthropicReasoning)
console.log('🔥 [Browser] =====================================')
resMessageIsDonePromise({ type: 'llmDone', toolCall, info: { fullText, fullReasoning, anthropicReasoning } }) // resolve with tool calls
},
onError: async (error) => {
// 日志：Browser端 - 错误
console.log('🔥 [Browser] LLM Error =====================================')
console.error('🔥 [Browser] Error:', error)
console.log('🔥 [Browser] =====================================')
resMessageIsDonePromise({ type: 'llmError', error: error })
},
onAbort: () => {
// stop the loop to free up the promise, but don't modify state (already handled by whatever stopped it)
console.log('🔥 [Browser] LLM Request Aborted')
resMessageIsDonePromise({ type: 'llmAborted' })
this._metricsService.capture('Agent Loop Done (Aborted)', { nMessagesSent, chatMode })
},
Expand Down
10 changes: 10 additions & 0 deletions src/vs/workbench/contrib/void/browser/convertToLLMMessageService.ts
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Expand Up @@ -594,6 +594,16 @@ class ConvertToLLMMessageService extends Disposable implements IConvertToLLMMess

const persistentTerminalIDs = this.terminalToolService.listPersistentTerminalIds()
const systemMessage = chat_systemMessage({ workspaceFolders, openedURIs, directoryStr, activeURI, persistentTerminalIDs, chatMode, mcpTools, includeXMLToolDefinitions })

// 日志：显示生成的系统消息
console.log('📋 [System Message Generated] =====================================')
console.log('📋 [System Message Generated] Chat Mode:', chatMode)
console.log('📋 [System Message Generated] Workspace Folders:', workspaceFolders)
console.log('📋 [System Message Generated] Active URI:', activeURI)
console.log('📋 [System Message Generated] System Message Length:', systemMessage?.length || 0)
console.log('📋 [System Message Generated] System Message Preview:', systemMessage?.substring(0, 500) + (systemMessage?.length > 500 ? '...' : ''))
console.log('📋 [System Message Generated] =====================================')

return systemMessage
}

Expand Down
14 changes: 13 additions & 1 deletion src/vs/workbench/contrib/void/browser/toolsService.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -203,6 +203,7 @@ export class ToolsService implements IToolsService {
is_regex: isRegexUnknown,
page_number: pageNumberUnknown
} = params
console.log('[toolsService] validateParams.search_for_files called', { queryUnknown, searchInFolderUnknown, isRegexUnknown, pageNumberUnknown });
const queryStr = validateStr('query', queryUnknown)
const pageNumber = validatePageNum(pageNumberUnknown)
const searchInFolder = validateOptionalURI(searchInFolderUnknown)
Expand Down Expand Up @@ -295,27 +296,37 @@ export class ToolsService implements IToolsService {

this.callTool = {
read_file: async ({ uri, startLine, endLine, pageNumber }) => {
console.log('[read_file] callTool entry', { uri: uri.toString(), startLine, endLine, pageNumber });
await voidModelService.initializeModel(uri)
console.log('[read_file] after initializeModel');
const { model } = await voidModelService.getModelSafe(uri)
if (model === null) { throw new Error(`No contents; File does not exist.`) }
console.log('[read_file] got model', { hasModel: !!model });
if (model === null) {
console.error('[read_file] No contents; File does not exist.', uri);
throw new Error(`No contents; File does not exist.`)
}

let contents: string
if (startLine === null && endLine === null) {
contents = model.getValue(EndOfLinePreference.LF)
console.log('[read_file] getValue full', { length: contents.length });
}
else {
const startLineNumber = startLine === null ? 1 : startLine
const endLineNumber = endLine === null ? model.getLineCount() : endLine
contents = model.getValueInRange({ startLineNumber, startColumn: 1, endLineNumber, endColumn: Number.MAX_SAFE_INTEGER }, EndOfLinePreference.LF)
console.log('[read_file] getValueInRange', { startLineNumber, endLineNumber, length: contents.length });
}

const totalNumLines = model.getLineCount()
console.log('[read_file] totalNumLines', totalNumLines);

const fromIdx = MAX_FILE_CHARS_PAGE * (pageNumber - 1)
const toIdx = MAX_FILE_CHARS_PAGE * pageNumber - 1
const fileContents = contents.slice(fromIdx, toIdx + 1) // paginate
const hasNextPage = (contents.length - 1) - toIdx >= 1
const totalFileLen = contents.length
console.log('[read_file] pagination', { fromIdx, toIdx, fileContentsLen: fileContents.length, hasNextPage, totalFileLen });
return { result: { fileContents, totalFileLen, hasNextPage, totalNumLines } }
},

Expand Down Expand Up @@ -349,6 +360,7 @@ export class ToolsService implements IToolsService {
},

search_for_files: async ({ query: queryStr, isRegex, searchInFolder, pageNumber }) => {
console.log('[toolsService] search_for_files called', { queryStr, isRegex, searchInFolder, pageNumber });
const searchFolders = searchInFolder === null ?
workspaceContextService.getWorkspace().folders.map(f => f.uri)
: [searchInFolder]
Expand Down
121 changes: 114 additions & 7 deletions src/vs/workbench/contrib/void/electron-main/llmMessage/sendLLMMessage.impl.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -310,6 +310,16 @@ const _sendOpenAICompatibleChat = async ({ messages, onText, onFinalMessage, onE
// max_completion_tokens: maxTokens,
}

// 日志：显示发送给OpenAI API的完整请求
console.log('🔄 [OpenAI-Compatible API Request] =====================================')
console.log('🔄 [OpenAI-Compatible API Request] Provider:', providerName)
console.log('🔄 [OpenAI-Compatible API Request] Model:', modelName)
console.log('🔄 [OpenAI-Compatible API Request] Options:', JSON.stringify(options, null, 2))
if (separateSystemMessage) {
console.log('🔄 [OpenAI-Compatible API Request] System Message:', separateSystemMessage)
}
console.log('🔄 [OpenAI-Compatible API Request] =====================================')

// open source models - manually parse think tokens
const { needsManualParse: needsManualReasoningParse, nameOfFieldInDelta: nameOfReasoningFieldInDelta } = providerReasoningIOSettings?.output ?? {}
const manuallyParseReasoning = needsManualReasoningParse && canIOReasoning && openSourceThinkTags
Expand All @@ -333,12 +343,21 @@ const _sendOpenAICompatibleChat = async ({ messages, onText, onFinalMessage, onE
let toolId = ''
let toolParamsStr = ''

// 日志：记录即将发起的API调用
console.log('🌐 [API Call Starting] OpenAI Chat Completions Create')
console.log('🌐 [API Call] Endpoint: chat/completions')
console.log('🌐 [API Call] Full Request Options:', JSON.stringify(options, null, 2))

openai.chat.completions
.create(options)
.then(async response => {
_setAborter(() => response.controller.abort())

console.log('🌐 [API Response] OpenAI stream started successfully')

// when receive text
for await (const chunk of response) {
// 处理流式响应，不打印chunk日志
// message
const newText = chunk.choices[0]?.delta?.content ?? ''
fullTextSoFar += newText
Expand Down Expand Up @@ -370,18 +389,41 @@ const _sendOpenAICompatibleChat = async ({ messages, onText, onFinalMessage, onE
})

}

// 日志：记录OpenAI流结束
console.log('🌐 [API Response] OpenAI stream completed')

// on final
if (!fullTextSoFar && !fullReasoningSoFar && !toolName) {
console.log('❌ [OpenAI Error] Empty response from model')
onError({ message: 'Void: Response from model was empty.', fullError: null })
}
else {
const toolCall = rawToolCallObjOfParamsStr(toolName, toolParamsStr, toolId)
const toolCallObj = toolCall ? { toolCall } : {}

// 日志：记录OpenAI最终响应
console.log('✅ [OpenAI Final Message] =====================================')
console.log('✅ [OpenAI Final Message] Full Text:', fullTextSoFar)
console.log('✅ [OpenAI Final Message] Full Reasoning:', fullReasoningSoFar)
console.log('✅ [OpenAI Final Message] Tool Name:', toolName)
console.log('✅ [OpenAI Final Message] Tool Params:', toolParamsStr)
console.log('✅ [OpenAI Final Message] Tool Call Object:', toolCall)
console.log('✅ [OpenAI Final Message] =====================================')

onFinalMessage({ fullText: fullTextSoFar, fullReasoning: fullReasoningSoFar, anthropicReasoning: null, ...toolCallObj });
}
})
// when error/fail - this catches errors of both .create() and .then(for await)
.catch(error => {
// 日志：记录OpenAI错误
console.log('❌ [OpenAI Error] =====================================')
console.log('❌ [OpenAI Error] Error Object:', error)
console.log('❌ [OpenAI Error] Error Status:', error instanceof OpenAI.APIError ? error.status : 'N/A')
console.log('❌ [OpenAI Error] Error Message:', error.message || error.toString())
console.log('❌ [OpenAI Error] Error Stack:', error.stack)
console.log('❌ [OpenAI Error] =====================================')

if (error instanceof OpenAI.APIError && error.status === 401) { onError({ message: invalidApiKeyMessage(providerName), fullError: error }); }
else { onError({ message: error + '', fullError: error }); }
})
Expand Down Expand Up @@ -484,15 +526,28 @@ const sendAnthropicChat = async ({ messages, providerName, onText, onFinalMessag
dangerouslyAllowBrowser: true
});

const stream = anthropic.messages.stream({
const anthropicRequestOptions = {
system: separateSystemMessage ?? undefined,
messages: messages as AnthropicLLMChatMessage[],
model: modelName,
max_tokens: maxTokens ?? 4_096, // anthropic requires this
...includeInPayload,
...nativeToolsObj,
}

})
// 日志：显示发送给Anthropic API的完整请求
console.log('🤖 [Anthropic API Request] =====================================')
console.log('🤖 [Anthropic API Request] Provider:', providerName)
console.log('🤖 [Anthropic API Request] Model:', modelName)
console.log('🤖 [Anthropic API Request] Options:', JSON.stringify(anthropicRequestOptions, null, 2))
console.log('🤖 [Anthropic API Request] =====================================')

console.log('🌐 [API Call Starting] Anthropic Messages Stream')
console.log('🌐 [API Call] Endpoint: messages (streaming)')

const stream = anthropic.messages.stream(anthropicRequestOptions)

console.log('🌐 [API Response] Anthropic stream created successfully')

// manually parse out tool results if XML
if (!specialToolFormat) {
Expand All @@ -518,6 +573,8 @@ const sendAnthropicChat = async ({ messages, providerName, onText, onFinalMessag
}
// there are no events for tool_use, it comes in at the end
stream.on('streamEvent', e => {
// 日志：记录每个Anthropic流事件
console.log('🔄 [Anthropic Stream Event]', JSON.stringify(e, null, 2))
// start block
if (e.type === 'content_block_start') {
if (e.content_block.type === 'text') {
Expand Down Expand Up @@ -561,17 +618,31 @@ const sendAnthropicChat = async ({ messages, providerName, onText, onFinalMessag

// on done - (or when error/fail) - this is called AFTER last streamEvent
stream.on('finalMessage', (response) => {
// 日志：记录Anthropic最终响应
console.log('✅ [Anthropic Final Message] =====================================')
console.log('✅ [Anthropic Final Message] Raw Response:', JSON.stringify(response, null, 2))

const anthropicReasoning = response.content.filter(c => c.type === 'thinking' || c.type === 'redacted_thinking')
const tools = response.content.filter(c => c.type === 'tool_use')
// console.log('TOOLS!!!!!!', JSON.stringify(tools, null, 2))
// console.log('TOOLS!!!!!!', JSON.stringify(response, null, 2))
const toolCall = tools[0] && rawToolCallObjOfAnthropicParams(tools[0])
const toolCallObj = toolCall ? { toolCall } : {}

console.log('✅ [Anthropic Final Message] Processed - Full Text:', fullText)
console.log('✅ [Anthropic Final Message] Processed - Full Reasoning:', fullReasoning)
console.log('✅ [Anthropic Final Message] Processed - Tool Call:', toolCall)
console.log('✅ [Anthropic Final Message] =====================================')

onFinalMessage({ fullText, fullReasoning, anthropicReasoning, ...toolCallObj })
})
// on error
stream.on('error', (error) => {
// 日志：记录Anthropic错误
console.log('❌ [Anthropic Error] =====================================')
console.log('❌ [Anthropic Error] Error Object:', error)
console.log('❌ [Anthropic Error] Error Status:', error instanceof Anthropic.APIError ? error.status : 'N/A')
console.log('❌ [Anthropic Error] Error Message:', error.message || error.toString())
console.log('❌ [Anthropic Error] =====================================')

if (error instanceof Anthropic.APIError && error.status === 401) { onError({ message: invalidApiKeyMessage(providerName), fullError: error }) }
else { onError({ message: error + '', fullError: error }) }
})
Expand Down Expand Up @@ -777,21 +848,36 @@ const sendGeminiChat = async ({
let toolParamsStr = ''
let toolId = ''


genAI.models.generateContentStream({
const geminiRequestOptions = {
model: modelName,
config: {
systemInstruction: separateSystemMessage,
thinkingConfig: thinkingConfig,
tools: toolConfig,
},
contents: messages as GeminiLLMChatMessage[],
})
}

// 日志：显示发送给Gemini API的完整请求
console.log('🧠 [Gemini API Request] =====================================')
console.log('🧠 [Gemini API Request] Provider:', providerName)
console.log('🧠 [Gemini API Request] Model:', modelName)
console.log('🧠 [Gemini API Request] Options:', JSON.stringify(geminiRequestOptions, null, 2))
console.log('🧠 [Gemini API Request] =====================================')

console.log('🌐 [API Call Starting] Gemini Generate Content Stream')
console.log('🌐 [API Call] Endpoint: generateContentStream')

genAI.models.generateContentStream(geminiRequestOptions)
.then(async (stream) => {
_setAborter(() => { stream.return(fullTextSoFar); });

console.log('🌐 [API Response] Gemini stream created successfully')

// Process the stream
for await (const chunk of stream) {
// 日志：记录每个Gemini流响应块
console.log('🔄 [Gemini Stream Chunk]', JSON.stringify(chunk, null, 2))
// message
const newText = chunk.text ?? ''
fullTextSoFar += newText
Expand All @@ -815,17 +901,38 @@ const sendGeminiChat = async ({
})
}

// 日志：记录Gemini流结束
console.log('🌐 [API Response] Gemini stream completed')

// on final
if (!fullTextSoFar && !fullReasoningSoFar && !toolName) {
console.log('❌ [Gemini Error] Empty response from model')
onError({ message: 'Void: Response from model was empty.', fullError: null })
} else {
if (!toolId) toolId = generateUuid() // ids are empty, but other providers might expect an id
const toolCall = rawToolCallObjOfParamsStr(toolName, toolParamsStr, toolId)
const toolCallObj = toolCall ? { toolCall } : {}

// 日志：记录Gemini最终响应
console.log('✅ [Gemini Final Message] =====================================')
console.log('✅ [Gemini Final Message] Full Text:', fullTextSoFar)
console.log('✅ [Gemini Final Message] Full Reasoning:', fullReasoningSoFar)
console.log('✅ [Gemini Final Message] Tool Name:', toolName)
console.log('✅ [Gemini Final Message] Tool Params:', toolParamsStr)
console.log('✅ [Gemini Final Message] Tool Call Object:', toolCall)
console.log('✅ [Gemini Final Message] =====================================')

onFinalMessage({ fullText: fullTextSoFar, fullReasoning: fullReasoningSoFar, anthropicReasoning: null, ...toolCallObj });
}
})
.catch(error => {
// 日志：记录Gemini错误
console.log('❌ [Gemini Error] =====================================')
console.log('❌ [Gemini Error] Error Object:', error)
console.log('❌ [Gemini Error] Error Message:', error?.message || error.toString())
console.log('❌ [Gemini Error] Error Stack:', error?.stack)
console.log('❌ [Gemini Error] =====================================')

const message = error?.message
if (typeof message === 'string') {

Expand Down
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